Skip to main content
Glama
knaisoma

data-olympus MCP server

KB Propose Memory

kb_propose_memory

Propose a new memory: high-confidence proposals auto-commit, while low-confidence ones enter a pending queue for operator review. Supports optional evidence strings.

Instructions

Propose a new memory file. High confidence auto-commits and enqueues for push; low confidence enters the pending queue for operator review.

evidence: optional supporting-context strings (max 10 items, 500 chars each), rendered into the memory's frontmatter and surfaced by kb_pending.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsYesShort tags for the proposed memory.
textYesMarkdown memory text to propose.
evidenceNoOptional supporting evidence strings, max 10 items of 500 chars each.
confidenceYesCaller confidence in the proposal, from 0.0 to 1.0.
agent_identityYesHuman-readable agent identity for audit events.
source_sessionYesStable id of the agent session making the call.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate write and non-destructive behavior. The description adds value by detailing the auto-commit vs pending queue logic and evidence rendering, which is beyond the annotation hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two paragraphs covering main behavior and evidence details. It could be more structured with bullet points, but it is efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a write tool with two flows and 6 parameters, the description covers essential behavior and parameter details. It does not explain the output schema, but that is provided separately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds contextual meaning to the evidence parameter (rendered into frontmatter, surfaced by kb_pending) that is not present in the schema description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Propose a new memory file' and explains the two outcomes based on confidence, distinguishing it from siblings like kb_propose_edit which is for editing existing memories.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides guidance on when to use the tool based on confidence levels (high vs low) but does not explicitly contrast with sibling tools like kb_propose_edit or kb_get.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/knaisoma/data-olympus'

If you have feedback or need assistance with the MCP directory API, please join our Discord server